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Fixed typo on string 19 #5

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Fixed typo on string 19 #5

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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -16,13 +16,13 @@ The following images show an example of detection and segmentation results.
For image reconstruction code, please refer to https://github.com/gift-surg/NiftyMIC.

# Requirements
* A CUDA compatable GPU with memoery not less than 6GB is recommended for training. For testing only, a CUDA compatable GPU may not be required.
* A CUDA compatable GPU with memory not less than 6GB is recommended for training. For testing only, a CUDA compatable GPU may not be required.

* Tensorflow 1.12.0. Install it by typing `pip install tensorflow-gpu=1.12` or following instructions from https://www.tensorflow.org/install.

* NiftyNet 0.2.0. Install it by typing `pip install niftynet=0.2` or downloading the source files from https://github.com/NifTK/NiftyNet/releases/tag/v0.2.0.

* Demic (a tool to use NiftyNet) v0.1. Download the source files from https://github.com/taigw/Demic/releases/tag/v0.1 and add the path of Demic to PYTHONPATH environment variable.
* Demic (a tool to use NiftyNet) v0.1. Download the source files from https://github.com/taigw/Demic/releases/tag/v0.1 and add the path of Demic to `PYTHONPATH environment variable.

# How to use
* To get fetal brain detection and segmentation results, run `bash/inference.sh`. You need to edit the `PYTHONPATH` environment variable in that file so that it includes the path of NiftyNet and Demic.
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